E-commerce Product Data Feeds: What They Are and How to Optimize Them

E-commerce product data feeds: the foundation of multi-channel selling

An e-commerce product data feed is a structured file that contains your product information—titles, descriptions, prices, images, availability, identifiers, and attributes—formatted for submission to shopping channels. Feeds are the bridge between your product catalog and every platform where you sell or advertise online.

Without product feeds, your products cannot appear in:

• Google Shopping ads and free listings
• Facebook and Instagram shops and dynamic ads
• Amazon marketplace listings
• Pinterest shopping pins
• TikTok shop
• Comparison shopping engines like PriceGrabber or Shopzilla
• Affiliate networks and partner sites

Every time a shopper sees a product ad, clicks through to a product listing, or browses a marketplace category, a product feed made that visibility possible. Feed quality directly determines whether your products appear, how they rank, and how effectively they convert.

This guide covers the fundamentals: what feeds contain, how different channels format them, common errors that cause problems, and how to optimize your feeds for better performance.

For deeper dives into specific aspects, see our guides on product feed optimization and product feed management in 2026.

Common feed formats and channel requirements

Different shopping channels accept different feed formats and have varying requirements for product attributes. Understanding these differences is essential for multi-channel selling.

Google Shopping (Merchant Center)

Google Shopping is the largest product advertising platform and has specific feed requirements:

Accepted formats:

• Text feeds (TSV/CSV) with tab or comma delimiters
• XML feeds following Google's schema

Key requirements:

• Attribute names must use English with underscores (e.g., image_link, product_type)
• Products expire after 30 days without updates
• New products undergo data quality checks taking up to 72 hours
• GTINs are strongly recommended for better visibility

Required attributes:

For detailed Google Merchant Center guidance, see our article on Google Merchant Center feed optimization.

Facebook and Instagram (Meta)

Meta's Commerce platform powers Facebook Shops, Instagram Shopping, and dynamic ads:

Accepted formats:

• CSV and TSV files
• RSS XML and ATOM XML
• Google Sheets (direct connection)
• Excel (XLSX) for scheduled uploads

Technical specifications:

• Maximum file size: 4 GB
• Recommended limit: under 5 million products per feed
• Upload options: hourly, daily, or weekly schedules
• Two modes: "replace" (full refresh) or "update" (incremental changes)

Key differences from Google:

• Facebook accepts Google Shopping feeds but may require additional attributes
• Multi-value fields can use JSON-encoded values or flattened columns
• Product sets enable targeting specific product groups in ads

Other channels

Amazon: Uses flat file templates with category-specific requirements. See our guide on Amazon flat file templates.

Pinterest: Accepts RSS feeds and catalog uploads with Pinterest-specific attributes for rich pins.

TikTok Shop: Requires product catalogs with specific formatting for in-app shopping features.

Comparison engines: Most accept standard CSV/XML formats but have varying attribute requirements.

Feed optimization best practices

Optimized feeds perform dramatically better than basic submissions. Research shows that businesses implementing comprehensive feed optimization see 45% increases in impression share and 32% improvements in click-through rates.

Product titles

Titles are the most important feed element for search matching:

• Front-load key information: Brand, product type, and key attributes should appear early since titles are often truncated
• Include searchable attributes: Color, size, material, and model number help match shopper queries
• Follow channel guidelines: Google recommends 150 characters max; Facebook allows longer titles
• Avoid promotional language: "Best seller" or "Free shipping" can trigger disapprovals

Example structure: [Brand] [Product Type] [Key Feature] [Color] [Size]

Product identifiers

GTINs (Global Trade Item Numbers), MPNs (Manufacturer Part Numbers), and brand names are critical:

• Include GTINs whenever available: They enable better product matching and unlock additional features
• Use correct formats: GTIN-13 (EAN), GTIN-12 (UPC), GTIN-14, or ISBN
• Set identifier_exists correctly: Use "false" only for custom-made or unbranded products

For products without standard identifiers, see our guide on handling missing EAN and GTIN.

Images

Image quality significantly impacts click-through rates:

• Use high resolution: Minimum 100x100 pixels, but higher is better
• Show the actual product: No placeholders, lifestyle images as primary, or promotional overlays
• Provide multiple images: Additional images improve engagement
• Ensure accessibility: All image URLs must be crawlable and return valid images

Pricing and availability

Accuracy is non-negotiable:

• Match landing page prices exactly: Mismatches cause disapprovals
• Update frequently: Automate updates every 4-6 hours minimum
• Include sale pricing correctly: Use sale_price and sale_price_effective_date for promotions
• Sync inventory in real-time: Out-of-stock products showing as available frustrate customers

Product descriptions

Descriptions support both search matching and shopper decision-making:

• Include key specifications: Materials, dimensions, compatibility, care instructions
• Use natural language: Avoid keyword stuffing
• Differentiate from titles: Descriptions should add information, not repeat the title

Common feed errors and how to fix them

Feed errors cause product disapprovals, reducing your visibility and wasting advertising budget. These are the most common issues:

Price mismatches

Problem: Feed price does not match the price displayed on your landing page.

Causes: Delayed feed updates, currency conversion issues, promotional pricing not synced, regional pricing differences.

Solutions:

• Automate feed updates every 4-6 hours or more frequently
• Implement structured data markup for automatic price validation
• Ensure currency codes match between feed and website
• Use sale_price attributes for promotional pricing

Missing or invalid identifiers

Problem: Products rejected for missing GTINs, MPNs, or brand information.

Causes: Supplier data lacks identifiers, incorrect format, reused identifiers across products.

Solutions:

• Source GTINs from manufacturers or barcode databases
• Validate GTIN check digits before submission
• Set identifier_exists to "false" for genuinely unbranded products
• Never reuse identifiers across different products

Inventory discrepancies

Problem: Products show as in-stock when sold out, or vice versa.

Causes: Delayed inventory sync, overselling, warehouse system disconnects.

Solutions:

• Implement real-time or near-real-time inventory sync
• Set conservative stock thresholds
• Use availability attributes correctly (in_stock, out_of_stock, preorder, backorder)

Image quality issues

Problem: Products disapproved for image problems.

Causes: Broken image URLs, images too small, watermarks or promotional text, placeholder images.

Solutions:

• Validate all image URLs before submission
• Use images at least 800x800 pixels (1200x1200 recommended)
• Remove watermarks, logos, and promotional overlays from product images
• Ensure images show the actual product being sold

Incomplete product data

Problem: Products underperform or get disapproved due to missing information.

Causes: Supplier data gaps, incomplete catalog management, missing required attributes.

Solutions:

• Audit feed completeness regularly
• Prioritize filling required and recommended attributes
• Use enrichment tools to fill data gaps at scale

For troubleshooting Google-specific issues, see our guide on fixing Google Merchant Center disapprovals.

How Lasso improves feed quality

Feed quality depends entirely on the product data behind it. If your catalog has gaps, inconsistencies, or errors, those problems flow directly into your feeds and cause disapprovals, poor ad performance, and lost sales.

Lasso addresses feed quality at the source by improving your product data:

• Fill missing attributes: AI-powered enrichment adds missing specifications, materials, dimensions, and other attributes that feeds require
• Standardize values: Normalize size, color, and other attributes to consistent formats that channels expect
• Generate optimized content: Create SEO-friendly titles and descriptions that perform well in shopping ads
• Validate before publishing: Catch errors and gaps before they cause feed rejections

The result is cleaner feeds with fewer disapprovals, better ad performance, and less time spent fixing errors.

The feed quality workflow

1. Import product data from suppliers, PIMs, or existing catalogs
2. Clean and standardize attributes, values, and formats
3. Enrich missing information using AI and web data
4. Validate against channel requirements
5. Export optimized feeds to Google, Meta, Amazon, and other channels

This approach treats feed optimization as a data quality problem rather than a formatting problem—because that is what it actually is.

Getting started with better product feeds

If your feeds are underperforming or generating frequent errors:

Step 1: Audit current performance

• Review disapproval rates in Google Merchant Center and other channels
• Identify the most common error types
• Check attribute completeness across your catalog

Step 2: Prioritize fixes

• Address errors causing the most disapprovals first
• Focus on high-value products and categories
• Fix systematic issues (like missing GTINs) before one-off problems

Step 3: Implement automation

• Set up automated feed updates at appropriate intervals
• Implement validation checks before feed submission
• Create alerts for error spikes or disapproval increases

Step 4: Improve source data

• Fill gaps in product attributes
• Standardize values across your catalog
• Ensure pricing and inventory sync reliably

For teams ready to transform their feed quality, explore Lasso's capabilities or book a demo to see how AI-powered enrichment can improve your product data and feed performance.